Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import joblib
+# importer la liste des langues
+languages = joblib.load('languages.joblib')
+# Fonction de traduction
+def translate_text(text, model_choice, src_lang, tgt_lang):
+    if model_choice == "NLLB-200 (facebook)":
+        nllb_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", src_lang=src_lang, tgt_lang=tgt_lang)
+        result = nllb_translator(text)[0]["translation_text"]
+    elif model_choice == "Opus-MT-EN-FR (Helsinki-NLP)":
+        en_fr_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-fr")
+        result = en_fr_translator(text)[0]["translation_text"]
+    else:
+        fr_en_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-fr-en")
+        result = fr_en_translator(text)[0]["translation_text"]
+    return result
+
+# Interface Gradio
+demo = gr.Interface(fn=translate_text,
+       inputs=[gr.Textbox(label="Texte à traduire", placeholder="Entrez du texte en français ici..."),
+        gr.Radio(choices = ["NLLB-200 (facebook)", "Opus-MT-EN-FR (Helsinki-NLP)", "Opus-MT-FR-EN (Helsinki-NLP)"],label="Choisissez le modèle"),
+        gr.Dropdown(choices = languages, label = 'Source Language'),
+        gr.Dropdown(choices = languages, label = 'Target Language')],
+    outputs=gr.Textbox(label="Texte traduit"),
+    title="Traduction dans plusieurs langues",
+    theme='shivi/calm_seafoam'
+)
+
+demo.launch()